Literature DB >> 31696294

Computed tomography angiography-derived fractional flow reserve (CT-FFR) for the detection of myocardial ischemia with invasive fractional flow reserve as reference: systematic review and meta-analysis.

Baiyan Zhuang1, Shuli Wang1, Shihua Zhao2, Minjie Lu3.   

Abstract

OBJECTIVES: A method named computed tomography angiography-derived fractional flow reserve (FFRCT) is an alternative method for detecting hemodynamically significant coronary stenosis. We carried out a meta-analysis to derive reliable assessment of the diagnostic performances of FFRCT and compare the diagnostic accuracy with CCTA using FFR as reference.
METHODS: We searched PubMed, EMBASE, The Cochrane Library, and Web of science for relevant articles published from January 2008 until May 2019 using the following search terms: FFRCT, noninvasive FFR, non-invasive FFR, noninvasive fractional flow reserve, non-invasive fractional flow reserve, and CCTA. Pooled estimates of sensitivity and specificity with the corresponding 95% confidence intervals (CIs) and the summary receiver operating characteristic curve (sROC) were determined.
RESULTS: Sixteen studies published between 2011 and 2019 were included with a total of 1852 patients and 2731 vessels. The pooled sensitivity and specificity for FFRCT at the per-patient level was 89% (95% CI, 85-92%) and 71% (95% CI, 61-80%), respectively, while on the per-vessel basis was 85% (95% CI, 82-88%) and 82% (95% CI, 75-87%), respectively. No apparent difference in the sensitivity at per-patient and per-vessel level between FFRCT and CCTA was observed (0.89 versus 0.93 at per-patient; 0.85 versus 0.88 at per-vessel). However, the specificity of FFRCT was higher than CCTA (0.71 versus 0.32 at per-patient analysis; 0.82 versus 0.46 at per-vessel analysis).
CONCLUSIONS: FFRCT obtained a high diagnostic performance and is a viable alternative to FFR for detecting coronary ischemic lesions. KEY POINTS: • Noninvasive FFRCThas higher specificity for anatomical and physiological assessment of coronary artery stenosis compared with CCTA. • Noninvasive FFRCTis a viable alternative to invasive FFR for the detection and exclusion of coronary lesions that cause ischemia.

Entities:  

Keywords:  Computed tomography angiography; Coronary artery disease; Hemodynamics; Myocardial ischemia; Stenosis

Mesh:

Year:  2019        PMID: 31696294     DOI: 10.1007/s00330-019-06470-8

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  54 in total

1.  Heart Disease and Stroke Statistics-2016 Update: A Report From the American Heart Association.

Authors:  Dariush Mozaffarian; Emelia J Benjamin; Alan S Go; Donna K Arnett; Michael J Blaha; Mary Cushman; Sandeep R Das; Sarah de Ferranti; Jean-Pierre Després; Heather J Fullerton; Virginia J Howard; Mark D Huffman; Carmen R Isasi; Monik C Jiménez; Suzanne E Judd; Brett M Kissela; Judith H Lichtman; Lynda D Lisabeth; Simin Liu; Rachel H Mackey; David J Magid; Darren K McGuire; Emile R Mohler; Claudia S Moy; Paul Muntner; Michael E Mussolino; Khurram Nasir; Robert W Neumar; Graham Nichol; Latha Palaniappan; Dilip K Pandey; Mathew J Reeves; Carlos J Rodriguez; Wayne Rosamond; Paul D Sorlie; Joel Stein; Amytis Towfighi; Tanya N Turan; Salim S Virani; Daniel Woo; Robert W Yeh; Melanie B Turner
Journal:  Circulation       Date:  2015-12-16       Impact factor: 29.690

2.  Summary receiver operating characteristic curve analysis techniques in the evaluation of diagnostic tests.

Authors:  Catherine M Jones; Thanos Athanasiou
Journal:  Ann Thorac Surg       Date:  2005-01       Impact factor: 4.330

Review 3.  Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews.

Authors:  Johannes B Reitsma; Afina S Glas; Anne W S Rutjes; Rob J P M Scholten; Patrick M Bossuyt; Aeilko H Zwinderman
Journal:  J Clin Epidemiol       Date:  2005-10       Impact factor: 6.437

4.  Users' guides to the medical literature. III. How to use an article about a diagnostic test. B. What are the results and will they help me in caring for my patients? The Evidence-Based Medicine Working Group.

Authors:  R Jaeschke; G H Guyatt; D L Sackett
Journal:  JAMA       Date:  1994-03-02       Impact factor: 56.272

5.  Evaluation of fractional flow reserve in patients with stable angina: can CT compete with angiography?

Authors:  Xin Liu; Yabin Wang; Heye Zhang; Youbing Yin; Kunlin Cao; Zhifan Gao; Huafeng Liu; William Kongto Hau; Lei Gao; Yundai Chen; Feng Cao; Wenhua Huang
Journal:  Eur Radiol       Date:  2019-03-18       Impact factor: 5.315

6.  Usefulness of noninvasive fractional flow reserve computed from coronary computed tomographic angiograms for intermediate stenoses confirmed by quantitative coronary angiography.

Authors:  James K Min; Bon-Kwon Koo; Andrejs Erglis; Joon-Hyung Doh; David V Daniels; Sanda Jegere; Hyo-Soo Kim; Allison M Dunning; Tony Defrance; Alexandra Lansky; Jonathon Leipsic
Journal:  Am J Cardiol       Date:  2012-06-29       Impact factor: 2.778

7.  Noninvasive CT-based hemodynamic assessment of coronary lesions derived from fast computational analysis: a comparison against fractional flow reserve.

Authors:  Panagiotis K Siogkas; Constantinos D Anagnostopoulos; Riccardo Liga; Themis P Exarchos; Antonis I Sakellarios; George Rigas; Arthur J H A Scholte; M I Papafaklis; Dimitra Loggitsi; Gualtiero Pelosi; Oberdan Parodi; Teemu Maaniitty; Lampros K Michalis; Juhani Knuuti; Danilo Neglia; Dimitrios I Fotiadis
Journal:  Eur Radiol       Date:  2018-10-15       Impact factor: 5.315

8.  Diagnostic Accuracy of Computed Tomography-Derived Fractional Flow Reserve : A Systematic Review.

Authors:  Christopher M Cook; Ricardo Petraco; Matthew J Shun-Shin; Yousif Ahmad; Sukhjinder Nijjer; Rasha Al-Lamee; Yuetsu Kikuta; Yasutsugu Shiono; Jamil Mayet; Darrel P Francis; Sayan Sen; Justin E Davies
Journal:  JAMA Cardiol       Date:  2017-07-01       Impact factor: 14.676

9.  Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: the NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps).

Authors:  Bjarne L Nørgaard; Jonathon Leipsic; Sara Gaur; Sujith Seneviratne; Brian S Ko; Hiroshi Ito; Jesper M Jensen; Laura Mauri; Bernard De Bruyne; Hiram Bezerra; Kazuhiro Osawa; Mohamed Marwan; Christoph Naber; Andrejs Erglis; Seung-Jung Park; Evald H Christiansen; Anne Kaltoft; Jens F Lassen; Hans Erik Bøtker; Stephan Achenbach
Journal:  J Am Coll Cardiol       Date:  2014-01-30       Impact factor: 24.094

10.  Coronary plaque quantification and fractional flow reserve by coronary computed tomography angiography identify ischaemia-causing lesions.

Authors:  Sara Gaur; Kristian Altern Øvrehus; Damini Dey; Jonathon Leipsic; Hans Erik Bøtker; Jesper Møller Jensen; Jagat Narula; Amir Ahmadi; Stephan Achenbach; Brian S Ko; Evald Høj Christiansen; Anne Kjer Kaltoft; Daniel S Berman; Hiram Bezerra; Jens Flensted Lassen; Bjarne Linde Nørgaard
Journal:  Eur Heart J       Date:  2016-01-12       Impact factor: 29.983

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  11 in total

Review 1.  Small vessel coronary artery disease: How small can we go with myocardial revascularization?

Authors:  Maciej T Wybraniec; Paweł Bańka; Tomasz Bochenek; Tomasz Roleder; Katarzyna Mizia-Stec
Journal:  Cardiol J       Date:  2020-09-28       Impact factor: 2.737

Review 2.  Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning.

Authors:  Joyce Peper; Dominika Suchá; Martin Swaans; Tim Leiner
Journal:  Br J Radiol       Date:  2020-08-12       Impact factor: 3.039

3.  Influence of diabetes mellitus on the diagnostic performance of machine learning-based coronary CT angiography-derived fractional flow reserve: a multicenter study.

Authors:  Yi Xue; Min Wen Zheng; Yang Hou; Fan Zhou; Jian Hua Li; Yi Ning Wang; Chun Yu Liu; Chang Sheng Zhou; Jia Yin Zhang; Meng Meng Yu; Bo Zhang; Dai Min Zhang; Yan Yi; Lei Xu; Xiu Hua Hu; Guang Ming Lu; Chun Xiang Tang; Long Jiang Zhang
Journal:  Eur Radiol       Date:  2022-01-12       Impact factor: 5.315

Review 4.  The Role of Cardiac Computed Tomography in Heart Failure.

Authors:  Spencer S Kitchin; Venkat Sanjay Manubolu; Sion K Roy; Matthew J Budoff
Journal:  Curr Heart Fail Rep       Date:  2022-05-19

Review 5.  [Beyond Coronary CT Angiography: CT Fractional Flow Reserve and Perfusion].

Authors:  Moon Young Kim; Dong Hyun Yang; Ki Seok Choo; Whal Lee
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2022-01-21

6.  Impact of machine-learning CT-derived fractional flow reserve for the diagnosis and management of coronary artery disease in the randomized CRESCENT trials.

Authors:  Fay M A Nous; Ricardo P J Budde; Marisa M Lubbers; Yuzo Yamasaki; Isabella Kardys; Tobias A Bruning; Jurgen M Akkerhuis; Marcel J M Kofflard; Bas Kietselaer; Tjebbe W Galema; Koen Nieman
Journal:  Eur Radiol       Date:  2020-03-12       Impact factor: 5.315

7.  Coronary Computed Tomography Angiography in Diagnosing Obstructive Coronary Artery Disease in Patients with Advanced Chronic Kidney Disease: A Systematic Review and Meta-Analysis.

Authors:  Xingxing S Cheng; Suman Mohanty; Valery Turner; Domenico Mastrodicasa; Simon Winther; Dominik Fleischmann; Jane C Tan; William F Fearon
Journal:  Cardiorenal Med       Date:  2020-12-15       Impact factor: 4.360

8.  Prediction of 3D Cardiovascular hemodynamics before and after coronary artery bypass surgery via deep learning.

Authors:  Gaoyang Li; Haoran Wang; Mingzi Zhang; Simon Tupin; Aike Qiao; Youjun Liu; Makoto Ohta; Hitomi Anzai
Journal:  Commun Biol       Date:  2021-01-22

9.  Functional Assessment of Cerebral Artery Stenosis by Angiography-Based Quantitative Flow Ratio: A Pilot Study.

Authors:  Kangmo Huang; Weihe Yao; Juan Du; Fang Wang; Yunfei Han; Yunxiao Chang; Rui Liu; Ruidong Ye; Wusheng Zhu; Shengxian Tu; Xinfeng Liu
Journal:  Front Aging Neurosci       Date:  2022-02-01       Impact factor: 5.750

Review 10.  Machine Learning Quantitation of Cardiovascular and Cerebrovascular Disease: A Systematic Review of Clinical Applications.

Authors:  Chris Boyd; Greg Brown; Timothy Kleinig; Joseph Dawson; Mark D McDonnell; Mark Jenkinson; Eva Bezak
Journal:  Diagnostics (Basel)       Date:  2021-03-19
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